EMB Global
https://emb.globalAbout
EMB Global is an AI-powered technology platform founded in 2018 and based in Gurugram, Haryana, India. The company connects enterprises with a curated network of IT service providers through its full-stack, AI-driven "Operating System for outsourcing" called Aura. This platform combines proprietary artificial intelligence with specialized human expertise to create more efficient tech teams. EMB Global offers a wide range of customizable IT and digital services, including software development, web design, digital marketing, and emerging technologies like Web 3.0. Their proprietary AI agent, Aura, automates the delivery of complex tech projects, while their staff augmentation services help businesses quickly scale development teams. The company serves startups, enterprises, and agencies across 23 countries, focusing on markets in India, the MENA region, and the USA.
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Role Overview
We are looking for an AI Engineer to design, build, and ship production AI systems, including agentic AI applications, for enterprise clients. This is a hands-on engineering role: you will write production code, build and evaluate models and agents, and work closely with architects and product teams to take solutions from prototype to scale.
Key Responsibilities
Design and build agentic AI systems: agent workflows, tool/function-calling, memory, and human-in-the-loop patterns. Build and productionise RAG pipelines, prompt-based applications, and LLM integrations across providers. Develop and maintain data and ML pipelines: feature engineering, model training, evaluation, and monitoring. Integrate AI systems with enterprise applications (CRMs, ERPs, ITSM tools) via APIs, events, and MCP-based tool servers. Implement guardrails, prompt-injection defences, and evaluation frameworks to keep AI systems safe and reliable in production.
Write clean, tested, production-grade code and participate actively in code and design reviews.
Collaborate with architects, product managers, and delivery teams to translate requirements into working AI solutions. Troubleshoot and optimise AI systems for accuracy, latency, and cost in production.
Required Qualifications
8–12 years of hands-on software engineering experience, with a strong, unbroken technical track record. Hands-on experience building and shipping AI/ML systems in production, not just POCs.
Practical experience with agentic AI systems and at least one major agent framework (LangGraph, CrewAI, AutoGen, OpenAI Agents SDK, Bedrock Agents/Strands, or Semantic Kernel).
Experience with LLM/GenAI systems: RAG pipelines, prompt engineering, structured outputs, and tool calling across providers.
Strong Python skills (TypeScript/Node.js a plus), with production-grade testing, CI/CD, and API design practices. Working knowledge of ML fundamentals: model evaluation, feature engineering, and experimentation. Cloud-native experience on AWS and/or Azure: containers, serverless, event backbones, and vector databases. Understanding of LLM safety and reliability practices: guardrails, prompt-injection defences, and observability.
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